Honda is advancing a multi-fingered robotic hand that can perform detailed assembly tasks like screwdriving and connecting terminals, highlighting a fundamental shift in robotics: walking is now the easy part, but making robots manipulate objects designed for human hands remains extraordinarily difficult. The breakthrough reveals why the industry's technical focus has shifted from locomotion to dexterity, and what it will take for humanoid robots to truly replace human workers on factory floors.

What Makes Robot Hands So Difficult to Engineer?

For decades, roboticists treated robotic hands as simple extensions of conventional grippers, mechanical devices that could grab and hold objects with brute force. Honda's approach is fundamentally different. Rather than bolting a gripper onto a robot arm, the company has developed the mechanical hardware, control systems, and artificial intelligence together as an integrated system.

The challenge lies in what Honda researcher Kenichiro Sugiyama calls the "last millimeter." Even when a robot can navigate a factory floor and reach the right location, the precision required to manipulate real-world objects is staggering. Position adjustments measured in millimeters and force adjustments of only a few newtons can determine whether a task succeeds or fails. Tasks involving deformable, slippery, or difficult-to-handle objects, such as fabric or a wet glass, continue to challenge robotic systems.

"Many robotic hands currently entering the market remain essentially extensions of conventional grippers. Honda's approach has instead focused on developing the mechanical hardware, control systems and artificial intelligence together," explained Kenichiro Sugiyama, Honda researcher.

Kenichiro Sugiyama, Honda Researcher

Honda's latest multi-fingered hand is approximately the size of a human hand and combines strength, responsiveness, and precision. The company says the technology can reproduce most human hand movements and perform detailed tasks including screwdriving and connecting and disconnecting terminals. The company recently developed a new version using a proprietary transmission mechanism intended to combine greater strength with dexterity.

How Is Embodied AI Changing Robot Training?

Traditional artificial intelligence systems learn from text, images, or video data processed on computers. Embodied AI, by contrast, learns through physical interaction with the real world. When a robot physically manipulates an object, its sensors generate rich information about forces, textures, and resistance that no camera or text dataset can fully capture.

Honda combines real-world movements with simulation to train its robotic systems, creating a feedback loop where hardware precision directly improves AI training quality. Better hardware and control systems enable better AI training, while improvements in AI can subsequently improve robot control. This interdependence means that even small mechanical improvements can yield significant gains in robotic capability.

Steps to Solving the Manipulation Problem

• Integrated Design: Develop mechanical hardware, control systems, and AI together rather than treating the robotic hand as a separate component bolted onto an existing arm.
• Precision Engineering: Achieve millimeter-level position accuracy and force control measured in newtons, as small variations can determine success or failure in assembly tasks.
• Embodied Learning: Train robots through physical interaction with real objects and environments, combining real-world sensor data with simulation to improve dexterity and task performance.

Why This Shift Matters for Manufacturing

For the past two decades, roboticists focused heavily on locomotion, the challenge of making robots walk, balance, and navigate complex environments. Advances in learning-based artificial intelligence have made robotic walking increasingly commonplace, shifting one of the industry's major technical challenges from locomotion toward manipulation.

This transition has profound implications for manufacturing. Successfully solving the manipulation problem could expand the range of assembly operations robots can perform, particularly tasks requiring robots to manipulate tools and components originally designed for human hands. Many factory assembly tasks involve screwdriving, connecting terminals, inserting components, and handling delicate parts, all of which require the kind of dexterous control that Honda and other roboticists are now pursuing.

Honda's robotics research traces back decades to its development of bipedal robots and ASIMO, the humanoid robot that became a symbol of Japanese robotics innovation. Technologies developed through those programs have subsequently been applied to autonomous driving, mobility systems, and Honda's continuing robotics research. The company's pivot toward dexterous manipulation represents the next frontier in making robots genuinely useful in real-world manufacturing environments.